1. Field of the Invention
The field relates to contextual ad matching, particularly content-targeted online advertising.
2. Art Background
The Internet is an increasingly important media outlet. Thus, online advertising is growing rapidly. Search-based advertisers have dominated the industry, and their success has prompted expansion beyond displaying ads alongside search results.
One respected form of search-based advertising is keyword-targeted advertising, where ads are displayed based in part on user search terms. Practitioners of this type of advertising, among them the largest search engines, have introduced strategies that attempt to match ads with user interests on non-search pages. Typically these content-targeted advertising strategies use Web page content as a proxy for user interest and match ads to content. A typical page involves much more information than a typical search query, and thus the content-targeted strategies tend to be much more complex than keyword-targeted strategies.
Current models for content match aim to match relevant advertisements to Web pages, through the unsupervised analysis of the page content. It is widely known among practitioners of content-targeted advertising that relevance is important. First, high congruency has been shown to increase click through rates and thereby profits. (Yoo, C. Y. “Preattentive Processing of Web Advertising”, PhD Thesis, University of Texas at Austin, 2006). Second, proposals for improved targeting methods have cited research showing that users view irrelevant ads as annoyances. (Ribeiro-Neto, B. N., Cristo, M. Golgher, P. B., De Moura, E. S. “Impedance Coupling in Content-Targeted Advertising.” Proceedings of the 28th Annual ACM SIGIR Conference. ACM Press. 2005.) Third, placing ads that are judged relevant, but are crossly inappropriate can pose a danger to the brands of both the ad distributor and the ad publisher.
Despite the importance of relevance, content-targeting systems currently in use place irrelevant ads. Even leading edge systems often make poor placements when the ad and page are topically related, but for some reason inappropriate. Misplacements are also common when few ads are classified as related to the web page topic. (Lacerda, A., Cristo, M., Conçalves, M. A., Fan, W., Ziviani, N., and Ribeiro-Neto, B. N. “Learning to Advertise”, Proceedings of the 29th Annual ACM SIGIR Conference. ACM Press. 2006.) Contextual advertising systems are ill equipped to determine the appropriateness of an ad, because often an ad that is inappropriate (e.g., an ad of a product placed in the Web page of its direct competitor) may be highly topically relevant.
Ribeiro-Neto 2005 and Lacerda 2006 propose improvements to then-state-of-the-art content-targeting systems. The first set of improvement relies on incorporating additional terms into the matching process, in some cases derived from a probabilistic model. In the second paper, the improvement comes from optimization of the ads ranking function via genetic programming. Though both methods result in improvement over standard methods, neither directly addresses inappropriate ad placements.